I. Introduction

The
R language, a freely available environment for statistical computing
and graphics is widely used in many fields.
This "expert-friendly" system
has a powerful command language and programming environment, combined with
an active user community. We discuss how R is ideal as a platform to support
experimentation in mathematical statistics, both at the undergraduate and
graduate levels. Using a series of case studies and activities, we describe
how R can be utilized in a mathematical statistics course as a toolbox for
experimentation. Examples include the calculation of a running variance,
maximization of a non-linear function, resampling of a statistic, simple
Bayesian modeling, sampling from multivariate normal and estimation of power.
These activities, often requiring only a few dozen lines of code, offer
the student the opportunity to explore statistical concepts and experiment.
In
addition,
they provide an introduction to the framework and idioms available in this
rich environment.

IV. Acknowledgements

We are grateful
to Ken Kleinman
and Paul Kienzle for comments on an earlier draft of the manuscript, and
for the support provided by NIMH grant R01-MH54693
and a Career Development Fund Award from the Department of Biostatistics
at the University of Washington.